In this workshop paper we describe the use of Genetic Algorithms (GAs) to post-process machine discovered knowledge. We present an example where a GA can give results comparable to the best available alternative heuristics. We then discuss open issues in Post Processing examining prospects for incorporating work on more sophisticated measures of knowledge utility, local (Baldwin and Lamarckian) search and the selective repair of knowledge structures.

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